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• Genetic Factors associated with Conversion from Active Surveillance to Treatment for Prostate Cancer

  This is a genome-wide association study (GWAS) of conversion from active surveillance (AS) for prostate cancer (PC) to treatment. AS is the monitoring with screening tests and/or biopsies over time of men usually with low-risk, early-stage PC to avoid harmful side effects of PC treatment. "Conversion" refers to patients who withdraw from AS (switch to active treatment) due to changes in their cancer development, anxiety about delayed treatment, or other reasons. Patients who converted because of anxiety alone were censored in the GWAS analysis. The overall goal of this study is to develop an easily measurable, germline-based panel of genetic variants to aid in selecting PC patients appropriate for AS and/or the intensity of monitoring. In total, 6,324 PC patients from 28 collaborating institutions are included in this study. Patients are those with PC who are either on AS or who have previously converted from AS to treatment. In this study, 70% of all subjects were diagnosed with very low-risk, low-risk, or low-volume intermediate-risk PC (Kryvenko and Epstein, 2016; PMID: 26709152) and have been enrolled in an AS program. DNA was extracted from blood, saliva, or formalin-fixed, paraffin-embedded (FFPE) tissue collected from the study subjects at the participating sites. Genotyping, quality control processes, and imputation were performed at the Center for Inherited Disease Research (CIDR) at Johns Hopkins University. CIDR used the Illumina Infinium Multi-Ethnic Global Array (MEGA) version 1, which included genome-wide tag SNPs and 10,000 SNPs selected with custom content. Quality control and assurance (QC/QA) checks on genotyped data involved four domains: sample-level checks, batch effects, SNP-level checks, and preliminary association tests. Samples and SNPs passing the QC/QA checks were imputed to appropriate reference panels (HRC r1.1 for patients of European ancestry) using the Michigan Imputation Server (PMID: 27571263). Unmeasured genetic variants were imputed using the Trans-Omics for Precision Medicine (TOPMed) Imputation Server, with 97,256 reference samples and 308,107,085 SNPs. Variants with imputation quality (INFO) score < 0.3 were excluded, leaving a total of 22,691,641 SNPs successfully imputed. After QC steps, a total of 5,936 samples genotyped at CIDR remained for inclusion in the GWAS.

  Study phs002056

• Genomic Characterization of Duke Melanoma Brain Metastases

  Previous work has shown that melanoma brain metastases (MBM) have a unique molecular profile compared to extracranial metastases (ECM). Description of the biology of MBM and associations between biological features and clinical outcomes will facilitate the design of rational therapies for patients with MBM. To better characterize the molecular profile of MBM, we conducted whole exome sequencing (WES) and total RNA sequencing on MBM tissues obtained from an independent cohort of 14 patients from Duke University Medical Center. This cohort adds valuable patient samples to the field and enables strengthened investigation of somatic mutations and gene expression profiles within and between cohorts. The mutational landscape and gene expression of MBM from the Duke cohort resembled those previously reported in a previously published dataset of WES and RNA sequencing in MBM and matched ECM tissues from UT MD Anderson Cancer Center (Fischer et al., 2019 30787016). Duke MBM demonstrated similar rates of mutations in genes associated with melanoma, including BRAF, NRAS, and PTEN, as the MD Anderson cohort. Immune populations in MBM were similar between Duke and MD Anderson MBM, though Duke samples demonstrated more resting CD4+ memory T cells. The ratio of M2 to M1 macrophages in the Duke cohort was similar to that of the MD Anderson cohort. In MBM, a higher M2:M1 ratio may contribute to an immune-suppressive tumor microenvironment. Sequencing data and sample attributes from MBM tissues obtained from 14 patients from Duke University Medical Center will be available through dbGaP.

  Study phs003009

• An autoinflammatory RIG-I variant causing Singleton-Merten Syndrome associates with small non-coding Y-RNAs

  The RNA sensor RIG-I performs a critical role in surveying the cytoplasm for the presence of viral nucleic acids and initiating the downstream anti-viral type I interferon pathway. Through recognition of specific features, such as the presence of a 5’ di/triphosphate motif or highly structured base-paired regions, RIG-I effectively differentiates between RNA of viral- and self-origin. In Singleton-Merten syndrome (SMS), gain-of-function variants in RIG-I lead to a breakdown in this surveillance system and results in aberrant sensing of self-RNAs and deleterious upregulation of type I interferons. The identity of the self-RNAs binding to gain-of-function RIG-I mutants has remained elusive and would provide a greater understanding of the aetiology of SMS. Here we used an infrared individual-nucleotide resolution UV-crosslinking and immunoprecipitation (irCLIP) approach to determine the RNA profile bound to a previously characterised ATPase-deficient SMS variant, RIG-IC268F. irCLIP identified a broad array of self-RNAs, primarily those transcribed by RNA polymerase III, that were bound to RIG-I. Subsequent native RNA immunoprecipitation confirmed a prominent and specific interaction between RIG-IC268F and Y-RNAs, a family of four structurally similar non-coding RNAs. Manipulation of Y-RNAs alone by targeting either Y-RNA transcripts or Y-RNA stabilising proteins was insufficient to negate RIG-I induce interferon, hinting at a broader profile of RNA polymerase III-derived RNAs being influential in driving the sterile activation of gain-of-function RIG-I variants.

  Study EGAS50000001660

• Emirati Phased Diploid Trio-Assemblies

  This study, conducted under the Emirati Genome Project, aims to build a foundational pangenome reference to enable precision medicine in the United Arab Emirates. We generated phased diploid genome assemblies for 27 Emirati nationals using deep PacBio HiFi sequencing and a trio-based assembly procedure. In total, this produced 54 haplotype-resolved assemblies representing maternal and paternal genomes for each participant. The resulting high-quality reference captures population-specific genetic diversity and will accelerate translational research, variant interpretation, and genome-informed healthcare in the region.

  Study EGAS50000001234

• Next generation sequencing of sporadic schwannomatosis samples

  Schwannomatosis (MIM #162091) is characterized by the development of multiple schwannomas without vestibular nerve involvement (which is a characteristic of neurofibromatosis type 2 - NF2). In an effort to detect novel genetic alterations predisposing to schwannomatosis, we sequenced eight tumor-blood DNA pairs from de novo schwannomatosis patients. The results of our study are present in the paper "Whole exome sequencing reveals that the majority of schwannomatosis cases remain unexplained after excluding SMARCB1 and LZTR1 germline variants" published in Acta Neuropathologica (PMID:25008767)

  Study EGAS00001000767

• Comparison of EGF and PDGF driven glioblastomas.

  Glioblastoma multiforme (GBM) is the most common and aggressive type of primary brain tumor. Epidermal growth-factor (EGF) and platelet-derived growth-factor (PDGF) receptors are frequently amplified and/or possess gain-of-function mutations in these tumors. Despite years of research into tyrosine-kinase inhibitors, clinical trials have shown disappointing efficacy. One of the underlying reasons is intra-tumor heterogeneity. To assess the effect of intra-tumor heterogeneity on gene expression, we derived a general approach to map single-cell expression profiles to sequentially-acquired mutations identified from exome sequencing. Using 288 single cells, we constructed high-resolution phylogenies of EGF-driven and PDGF-driven GBMs, modeling transcriptional kinetics during tumor evolution. A deletion in a PDGF-receptor domain involved in dimerization correlated to an up-regulation of the PI3K/AKT pathway in a proneural GBM, and ectopic expression of this mutant PDGFRA in vitro enhanced proliferation and invasiveness. Descending the phylogenetic tree of the PDGFR-driven tumor corresponded to a progressive induction of an oligodendrocyte progenitor-like cell type that expresses growth and angiogenic factors. In contrast, phylogenetic analysis of an EGFR-amplified tumor showed a gradual up-regulation of pro-invasive genes.

  Study EGAS00001001900

• Rituximab-treated lymphoma patients show correlated deficiency in serological and T cell Spike-specific response after SARS-CoV-2 vaccination: insights from the CORSA Study.

  This study is part of the CORSA trial (NCT04345315), a prospective multicentric research project conducted by the Istituto Romagnolo per lo Studio dei Tumori “Dino Amadori” to investigate the immunologic response to mRNA SARS-CoV-2 vaccines in patients with hematologic malignancies (HM) and healthy individuals as controls (HC). The data in this repository refer to two subcohorts: 7 healthy controls and 10 lymphoma patients, randomly selected. Whole blood samples were collected to characterize T cell receptor (TCR) repertoire specificity against SARS-CoV-2 proteins before and after two BNT162b2 vaccination cycles, at baseline (before vaccination), 50 days after the first dose (V1), and 6 months after the first dose (V3). All participants were vaccinated under the Italian national campaign and provided informed consent following the Declaration of Helsinki. We investigated SARS-CoV-2-specific T cell responses through TCR repertoire profiling and examined correlations between serological and cellular responses in both patient and control groups. Using Next-Generation Sequencing (NGS) to characterize the CDR3 sequences of TCR β-chains from peripheral blood, we assessed clonal expansion (depth) and diversification (breadth) of SARS-CoV-2-specific T cell clonotypes over time, aiming to understand how cancer and its treatment influence vaccine-induced immunity in immunocompromised individuals.

  Study EGAS50000001205

• Chracterising_cellur_pathways_underlying_CD3_CD28_activation_of_human_CD4__cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001004147

• Chracterising_cellur_pathways_underlying_CD3_CD28_activation_of_human_CD4__cells

  We devised an approach to disentangle the TCR and CD28 pathways upon stimulation in naive and memory primary human CD4+ T cells (Tcons) in response to defined stimulatory signals. Sorted Tcons were activated using a titration of anti-CD3 and anti-CD28 in combination as well as individually. As a control we cultured cells in the same conditions but without the stimuli. In total, we defined seven conditions from four individuals for sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002438

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

  Study phs001442